Investigation of independent reinforcement learning algorithms in multi-agent environments

HIGHLIGHTS

• who: Ken Ming Lee from the Politecnico di Milano, Italy Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada have published the Article: Investigation of independent reinforcement learning algorithms in multi-agent environments, in the Journal: (JOURNAL)
• what: The authors investigate the empirical performance of independent algorithms in multi-agent settings, and compare them to various multi-agent algorithms under the Centralized Training and Decentralized Execution scheme (Oliehoek et_al, 2008; Kraemer and Banerjee, 2016). The authors evaluate these algorithms on 7 multi-agent environments from the PettingZoo library (Terry et_al, 2020b), which . . .
  

   

  

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